Category: science

Hypothesis testing first starts with theory. Theories are particular assumptions about the way things are. After a theory is formulated, a conceptual hypothesis is created, which is a more specific (than pure theory) prediction about the outcome of something. Next an experimental hypothesis is created. This is where definitions are operationalized so specific matters can be tested. For example, you could operationalize affection as number of hugs and kisses and other related actions. Then you statistically hypothesize in order to measure and test one of two hypotheses: the null, or H0, which represents non-effect (i.e. no difference between samples or populations, or whatever was tested), and an alternate hypothesis, H1.

The alternate hypothesis is that there is a difference, or an effect. It can be that one mean is greater than another, or that they are just not equal. So, the purpose of statistical testing is to test the truth of a theory or part of a theory. In other words, it is a way to look at predictions to see if they are accurate. To do this, researchers test the null hypothesis. We do not test the alternate hypothesis (which is what we think will happen). We do this because we base our testing on falsification logic (i.e., it only takes one example to prove a theory is wrong but conversely you cannot prove that a theory is right without infinite examples, so we look for examples where we are wrong).

The probability associated with a statistical test is assigned to the possibility of the occurrence of Type I error. This is the probability that you will reject the null hypothesis when in fact the null is true and thus should not have been rejected. It is saying there was an effect or a difference when there really was not.

The process of statistical testing can result in probability statements about the theories under consideration but only under certain conditions. Statistical testing and hypothesizing is representative of theory when it is conceptually (verbally and operationally) connected to theory. This means that there has to be a logical and direct association between the statistical probability statements and the theory in order for those statements to represent the overarching theory. This link is forged by the experimental and conceptual hypotheses.

Statistics are used by all but understood by few. In fact, studies have shown that 94% of people have little to no understanding of statistical methods. OK, that last statistic was made up; I wrote it to make a point though. I could post something like that on this blog and people would believe it and possibly even repeat it. The sad thing is that it probably isn’t that far from reality. In social science and neuroscience research we use statistics to understand data and support hypotheses. This post will serve as a statistical primer. I will not discuss how to calculate statistics, rather I will write about the underlying assumptions and theory of statistics. I will also discuss how to properly use and understand them (and hopefully avoid misusing them). I hope to help you become a more informed consumer of statistics.

When did we start using statistics and why?

Joel Best wrote a brief history of the use of statistics in his excellent book Damned Lies and Statistics: Untangling Numbers From the Media, Politicians, and Activists. [I urge everyone to read the book to be more informed about statistics. All quotes will be from the book. It provides only a superficial treatment of actual statistical methods – which he states is the case – but it provides a good theoretical background for being a critical thinker about statistics]. He states that statistics rose in popularity as governments and social activists wanted ways to track and “influence debates over social issues” (p.11). Early statistics were used almost exclusively for political purposes, especially to shape social and governmental policies. From the beginning, statistics were used for non-neutral purposes. They gave credibility to arguments.

One assumption that people erroneously make is that statistics are neutral and that they represent truth. They are useful for aggregating a lot of data but the problem is that most statistical methods are based on certain assumptions about the underlying data (e.g., that it is normally-distributed). However, many times researchers use certain statistical methods and make conclusions based on those data when the methods are not appropriate for the data. Even simple descriptive statistics (e.g., averages) can lead to people making erroneous conclusions.

People who create statistics all have a purpose for them. Researchers are all biased and have agendas. It just may be to get their research published or it might be for other ulterior reasons. Social activists use statistics to create social problems (see p. 14); they are not the cause of the “problem” but they try to raise awareness of it by turning it into a “problem” that we need to pay attention to and solve. This can often be a good thing but activists are using statistics to give credibility to their cause (e.g., “According to the World Health Organization, between 12 percent and 25 percent of women around the world have experienced sexual violence at some time in their lives.” source). Governments also use statistics to defend their position (e.g., “Crime rates decreased by XX% from last year. See! we are doing our job.”) and sometimes to counter the claims of activists.

The media pick up on statistics, on activists, because they present a new story and might even be controversial and controversy sells. Businesses also use statistics to promote their causes. Not everyone or entity will collect data in the same way either – one police station might have different criteria for counting an assault than another one has.

The author Best proposes three general questions to ask when seeing a statistic used.

Who created this statistic?

Why was this statistic created?

How was this statistic created? (pp. 27-28).

Many times people don’t even know enough to ask those questions or to research the answers to those questions. After all, as Best points out, we are largely an innumerate society (this holds true world-wide). Innumeracy is the math equivalency of illiteracy. A majority of people are uncomfortable with even basic mathematics and completely oblivious to statistics. After all, mathematics is abstract and requires a lot of mental effort to use and understand. It is often not taught as well as it can and only reluctantly learned in school. Once out of school, people rarely need to use more than basic math and so they forget what they learned. The other problem that we have is that we accept math (and by extension, statistics) to be perfect and infallible (Gödel demonstrated in effect that this is not the case). Best describes this fallacy:

“We sometimes talk about statistics as though they are facts that simply exist, like rocks, completely independent of people, and that people gather statistics much as rock collectors pick up stones. That is wrong. All statistics are created through people’s actions: people have to decide what to count and how to count it, people have to do the counting and the other calculations, and people have to interpret the resulting statistics, to decide what the numbers mean. All statistics are social products, the results of people’s efforts” (p.27; emphasis added).

So what do you do when you view a news program on TV or read an article or hear an activist or politician quote a statistic? If it makes you go, “Wow!” then that is one sign you need to step back and really scrutinize it (which you should do even if it doesn’t surprise/scare/etc. you). If you agree with the point the show, article, or person is trying to make then you really need to step back and critique the statistic. This means you need to understand your biases. It is easy to only want to confirm our hypotheses and beliefs and ignore anything that might contradict them. This is generally adaptive to help us process a lot of information but it can be a problem when we don’t critically view statistics, especially when they are “bad statistics” (which you can never discover without critiquing them). When you view or read a statistic, that is the time to ask yourself those 3 questions Best proposed and go from there. You might discover something interesting.

I’m going to preface my post by stating that the following post was written to help me think through the relationship between neuroscience and therapy. As such, it is a philosophical journey through some of my thoughts and is not even necessarily what I really believe because I’m still working on discovering what I believe. Thought processes like this are one way I try to keep some of my beliefs about psychology and neuroscience balanced. If I start leaning too strongly one way, I’ll start looking for things that disconfirm those beliefs and see what I discover. It’s a bit of playing the Devil’s Advocate with myself and a bit of philosophizing. Some of my friends and I used to do things like this in junior high and high school – having philosophical discussions where we discussed things and even tried to argue for things that we didn’t necessarily believe (e.g., classic topics such as supposing that this world and universe really aren’t real but are just reflections of reality. Again, that’s not something I believe but we would speculate). What does this all have to do with psychology and neuroscience?

The brain is what drew me to psychology initially. However, I vowed I would never go into clinical psychology because I didn’t think I would like therapy or dealing with people’s problems. Over time I discovered neuropsychology. Most neuropsychologists are clinical psychologists so in order or me to be a neuropsychologist, I had to be trained as a clinical psychologist. There are many things I enjoy about clinical psychology but therapy is not one of those things. Granted, most neuropsychologists do not actually do therapy, but we have to be trained in it. I enjoy talking with people in sessions but I haven’t been that impressed with therapy as a whole so far. Maybe that’s just because I haven’t exactly found the particular type of therapeutic method that really “clicks” with me. Cognitive-behavioral therapy is fine but so much of actual therapy in practice is just plain common sense. However, not everyone has a lot of common sense so they need some training in it. Part of me recognizes the validity of therapy but another part of me struggles with it. Now on to my main article.

The more I study the brain and the more exposure I have to therapy (giving, not receiving), the more biased towards the brain I become. What I mean is that we continue to discover more about the brain and as we discover more, the more behavior we can explain based on biology or neurophysiology and the less important I think therapy is. I’ve written about this topic in the past but wanted to briefly revisit it. This is somewhat of a second chapter to that post. Before I continue I wanted to expose one of my biases; I believe humans have free will. Even though some of my beliefs about the brain could be seen as mechanistic and deterministic, I do not believe that a strongly-biological foundation for behavior rules out free will. You can still assume biological foundations without assuming determinism. If, for example, you have a monistic set of assumptions that incorporates both mind – “nonmaterial” – and body – “material” – in one. [I have quotes around nonmaterial and material because mind is not necessarily nonmaterial and body is not necessarily material, well at least philosophically speaking]. Monism is a similar idea to a unified field theory (e.g., Grand Unified Theory) or the Theory of Everything for which some theoretical physicists are searching. That’s not what I’m going to write about and if it didn’t make sense, then don’t worry about it (I discussed this topic in a couple different posts: here {I linked to that post previously} and here). To summarize, I view behavior through a strong biological bias but I do not assume determinism.

As I said earlier, the more I learn about the brain and behavior (through research and observation), the more I lean towards neuroscience and away from “traditional psychology.” However, I still appreciate the psychosocial aspects of behavior; the nature versus nurture dispute will never be resolved because both are important. The environment is important – all external stimuli are important – but the problem with downplaying biology is that it is the medium of behavior. What I mean is, everything we think, sense, perceive, or do is translated and transmitted through the firing of neurons. This means that all abnormal behavior, which is what psychologists often are interested in, originates in a neuron or related cell. Whether or not the cause of that behavior was internal or external is irrelevant. All events and stimuli are translated into patterns of neuronal firings.

This is why I think that understanding the biology of the brain is the best way to understand a person’s behavior. However, because we have an imperfect understanding of the biology of the brain, we have an imperfect understand of the biological foundations of behavior. This means that until we have a perfect understanding, we cannot ignore the psychosocial aspects of behavior; even with a perfect understand we couldn’t either because even if we understand the “translation” process we may not understand the origin of what needs to be translated. This is where traditional talk therapy can be most beneficial. However, I still believe less and less that talk therapy is the best solution for dealing with many psychological issues. Over time as we discover more and more about the brain, therapy will become even less important.

That is a fairly radical position to take as a student of clinical psychology – it’s more in line with psychiatry, or rather, I believe it’s more in line with neuroscience. I’m not saying that therapy is useless, I’m just saying that as we gain a more perfect understanding of the brain and how various chemicals interact in the brain, we will have less need for people to help others by “talking” through their problems. The better we understand the physiology of the brain, the more natural our pharmaceuticals will be. In other words, it will be easier to mimic and create normal brain functioning. Of course, many will ask, “What is normal?” That’s a good question.

Some may argue that with depression, for example, many people will have negative image and self-evaluations, which can lead to depression. That is true but it’s the classic chicken and egg question. Which came first? Did the negative thoughts cause the depression or did the person experiencing negative thoughts have a biological predisposition to those thoughts and depression? In other words, it is possible that biology originally led to the negative thoughts and not vice versa. This is all speculation but I think there is increasing evidence for this view.

The big problem with my point though is that at some point, it does become a deterministic system in that it’s possible that we could medicate away people’s free will. This is an unacceptable outcome. There would be a lot of power with this knowledge and many opportunities for abuse. That’s an ethical discussion for a later time.

To summarize, I think that as we (speaking in the collective) gain a more perfect understanding of the brain (and even individual differences in the brain) we will be better able to eradicate and prevent many or most psychological disorders. We could potentially stop schizophrenia through genetic engineering or other modifications. Again, I’m not addressing whether or not we should but I believe we will have the ability to at some point. This is why, at the moment I lean more towards neuroscience than I do psychotherapy. Of course, tomorrow I could [I won’t] write a post that completely contradicts this one. As I said, this is a process. I think it’s important to argue both sides of the issue.

I wrote this response to someone who questioned the assertion I made (on a different website) that science is not impartial. Let me know what you think.

I don’t really have room or time to get into a philosophical discussion; this is a discussion that takes months to talk about. As a note, I’m not just making things up, I’ve studied epistemology in college. One of the philosophical foundations of science (science is all based on philosophy, which is one reason in the U.S. all science doctorates are PhDs – Doctor of Philosophy) is empiricism. I’ll quote from Wikipedia because in this case it is accurate.

“Empiricism is one of several competing views about how we know things, part of the branch of philosophy called epistemology, or “theory of knowledge”. Empiricism emphasizes the role of experience and evidence, especially sensory perception, in the formation of ideas, while discounting the notion of innate ideas.”

“In the philosophy of science, empiricism emphasizes those aspects of scientific knowledge that are closely related to evidence, especially as discovered in experiments. It is a fundamental part of the scientific method that all hypotheses and theories must be tested against observations of the natural world, rather than resting solely on a priori reasoning, intuition, or revelation. Hence, science is considered to be methodologically empirical in nature.”

There are other competing philosophies to empiricism. Rationalism is one of those; although in our day some ideas of rationalism are combined with empiricism. Materialism (all entities are matter and reducible to smaller entities, e.g., atoms) is another foundation for most science.

Because modern science is based on specific philosophies with specific assumptions (e.g., that all is matter) it cannot be completely impartial because science (forgive the anthropomorphism) inherently disregards anything that is not based on its same assumptions and philosophies (e.g., religion). Science has one particular view of the world and states that everything else is false, or at least unknowable. That’s not impartial – that’s bias. That’s like Americans saying “Our world view is the only correct world view.” Now, maybe it is true but that does not make it less biased. Everything and everyone have biases, even the philosophies that form the foundation for science.

As I said, this is some pretty deep philosophy. People have been arguing over this for thousands of years and will be for thousands more.

One last example. We tend to believe that mathematics is perfect and unbiased. Kurt Godel showed that it isn’t. Now, not everyone agrees with his ideas but he convincingly showed that most math is flawed, or at least incomplete. Math does not equal science but most science is founded on mathematical principles.

I answered your question, hopefully without coming across as a troll. As I said in my original post, I’m not trying to discredit science (science is my job) but blindly accepting that science is perfect and completely unbiased and the only way to knowledge is demonstrating as much faith in science as many do in religion.”

After a reply back that expressed complete disbelief (that also insulted my intelligence) 🙂 here’s my final response:

“I did not say that philosophy and science are the same, I just said that science is based on specific philosophies. As I said, it’s some pretty heavy stuff that most people (rightly) don’t care about. Again, I didn’t say philosophy and science are the same. The relationship (and this isn’t a perfect example) is more like philosophy:science::arithmetic:calculus.”

Am I completely off base here? I haven’t had extensive epistemology but I’ve had a fair amount. I remember in one of my classes that some people just didn’t get it. They were very bright people, it’s just that philosophy requires a different way of thinking (not better, just different). It takes practice; I just happened to start having serious philosophical discussions with friends pretty early on in school.